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+--- Thread: 8B vs 14B sweet spot (/showthread.php?tid=1116)
8B vs 14B sweet spot - lablab - 10-12-2026
Thought I'd post a small recipe because a lot of threads ask similar things.
Maybe useful as a starting point: vLLM on GB200, keeping KV cache pressure in mind from the start.
If someone wants the exact settings I can clean them up and post them.
My use case is pretty ordinary: local chat, some document work, and occasional batch jobs.
Re: 8B vs 14B sweet spot - latentscope35 - 10-12-2026
What worked for me was pretty simple. If you're on TensorRT-LLM, I'd confirm the version first and then reduce variables until the behavior is obvious. Not glamorous advice, but repeatable baselines save a lot of time.
Re: 8B vs 14B sweet spot - modgarden - 10-12-2026
Need a little more detail here. What model, what runtime, and roughly what context size?
Re: 8B vs 14B sweet spot - thetagrid15 - 10-13-2026
My first guess would be this: On GB200, the easiest win is often to back off the aggressive settings and see whether the problem survives. Once you know the plain path works, then add the faster path back in piece by piece.
Re: 8B vs 14B sweet spot - homelabhenry - 10-13-2026
I'd start with the simpler stack.
Re: 8B vs 14B sweet spot - quantyard - 10-14-2026
Good point. I ended up in about the same place using Ollama. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.
Re: 8B vs 14B sweet spot - cachelab - 10-14-2026
What worked for me was pretty simple. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at consumer GPUs.
Re: 8B vs 14B sweet spot - fastlab - 10-14-2026
Not sure I agree there. I get why that seems right, but on GB200 the bottleneck felt elsewhere. Worth testing the simpler explanation before adopting the more interesting one.
Re: 8B vs 14B sweet spot - edgekite - 10-14-2026
What worked for me was pretty simple. If you're on TensorRT-LLM, I'd confirm the version first and then reduce variables until the behavior is obvious.
Re: 8B vs 14B sweet spot - amberrunner - 10-14-2026
Quote:What worked for me was pretty simple. If you're on TensorRT-LLM, I'd confirm the version first and then reduce variables until the behavior is obvious
Good point. I ended up in about the same place using vLLM. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.